System, method, and computer-readable storage medium for traffic intersection navigation

ABSTRACT

A host vehicle includes a plurality of sensors communicably coupled to the host vehicle. Additionally, the host vehicle includes processing circuitry configured to map-match a location of the host vehicle in response to approaching a traffic intersection, receive traffic intersection information from the plurality of sensors in response to approaching the traffic intersection, the plurality of sensors having a predetermined field of view corresponding to a host vehicle field of view, estimate a driver field of view based on the host vehicle field of view, determine whether navigating through the traffic intersection is safe based on the driver field of view, and modify driver operation in response to a determination that navigation through the traffic intersection is not safe based on the driver field of view.

CROSS-REFERENCE TO RELATED APPLICATION

This application is related to Oblon Ref. No.: 515119US filed Jan. 4,2019 and Oblon Ref. No.: 515158US filed Jan. 4, 2019, which areincorporated herein by reference in their entirety.

BACKGROUND

The “background” description provided herein is for the purpose ofgenerally presenting the context of the disclosure. Work of thepresently named inventors, to the extent it is described in thisbackground section, as well as aspects of the description which may nototherwise qualify as prior art at the time of filing, are neitherexpressly or impliedly admitted as prior art against the presentinvention.

Generally, drivers do not check the behavior of other vehicles at atraffic intersection when they know they have priority at a signalizedor controlled intersection. For example, at traffic lights, when adriver has the green light, the driver commonly enters an intersectionwithout checking for the possibility that intersecting traffic mayviolate predetermined traffic patterns for that intersection (e.g., anintersecting vehicle runs a red light). As a result, crashes can happenwhen intersecting traffic is not visible or observed. Additionally,drivers may attempt to overtake a preceding vehicle despite one or moreoncoming vehicles being hidden by various obstacles. Further, in asimilar situation, drivers may not be prepared to avoid suddenslow-downs on highways. For example, when traveling on highways in fasttraffic, drivers may not be able to see or may not estimate the speed oftraffic as far ahead as they should. This can result in not beingprepared for unexpected and unmitigated slow-downs with a high risk ofcollision with one or more preceding vehicles.

SUMMARY

According to aspects of the disclosed subject matter, a host vehicleincludes a plurality of sensors communicably coupled to the hostvehicle. Additionally, the host vehicle includes processing circuitryconfigured to map-match a location of the host vehicle in response toapproaching a traffic intersection, receive traffic intersectioninformation from the plurality of sensors in response to approaching thetraffic intersection, the plurality of sensors having a predeterminedfield of view corresponding to a host vehicle field of view, estimate adriver field of view based on the host vehicle field of view, determinewhether navigating through the traffic intersection is safe based on thedriver field of view, and modify driver operation in response to adetermination that navigation through the traffic intersection is notsafe based on the driver field of view.

In another embodiment, a host vehicle includes a plurality of sensorscommunicably coupled to the host vehicle. Additionally, the host vehicleincludes processing circuitry configured to map-match a location of thehost vehicle in response to approaching a preceding vehicle, receiveovertaking information from the plurality of sensors in response to thehost vehicle approaching the preceding vehicle, the plurality of sensorshaving a predetermined field of view corresponding to a host vehiclefield of view, estimate a driver field of view based on the host vehiclefield of view, determine whether overtaking the preceding vehicle issafe based on the driver field of view, and modify driver operation inresponse to a determination that overtaking the preceding vehicle is notsafe based on the driver field of view.

In another embodiment, a host vehicle including a plurality of sensorscommunicably coupled to the host vehicle. Additionally, the host vehicleincludes processing circuitry configured to map-match a location of thehost vehicle while the host vehicle is operating on a highway, receiveobstruction information from the plurality of sensors, the plurality ofsensors having a predetermined field of view corresponding to a hostvehicle field of view, estimate a driver field of view based on the hostvehicle field of view, determine whether a speed of the host vehicle issafe based on the driver field of view and the obstruction information,and modify driver operation in response to a determination that thespeed of the host vehicle is not safe based on the driver field of view.

The foregoing paragraphs have been provided by way of generalintroduction, and are not intended to limit the scope of the followingclaims. The described embodiments, together with further advantages,will be best understood by reference to the following detaileddescription taken in conjunction with the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

A more complete appreciation of the disclosure and many of the attendantadvantages thereof will be readily obtained as the same becomes betterunderstood by reference to the following detailed description whenconsidered in connection with the accompanying drawings, wherein:

FIG. 1 illustrates an exemplary system configured for improving thesafety in various driving situations according to one or more aspects ofthe disclosed subject matter;

FIG. 2 illustrates an exemplary traffic intersection according to one ormore aspects of the disclosed subject matter;

FIG. 3 illustrates an algorithmic flow chart of a method for trafficintersection navigation according to one or more aspects of thedisclosed subject matter;

FIG. 4 illustrates an algorithmic flow chart of a method for determiningintersection priority according to one or more aspects of the disclosedsubject matter;

FIG. 5 illustrates an algorithmic flow chart of a method for receivingthe traffic intersection information according to one or more aspects ofthe disclosed subject matter;

FIG. 6 is an algorithmic flow chart of a method for mapping the hostvehicle field of view according to one or more aspects of the disclosedsubject matter;

FIG. 7 illustrates an algorithmic flow chart of a method for safelynavigating a traffic intersection according to one or more aspects ofthe disclosed subject matter;

FIG. 8A illustrates an overtaking area according to one or more aspectsof the disclosed subject matter;

FIG. 8B illustrates an overtaking area according to one or more aspectsof the disclosed subject matter;

FIG. 9 illustrates a host vehicle field of view of the host vehicle anda driver field of view of a driver according to one or more aspects ofthe disclosed subject matter;

FIG. 10 is an algorithmic flow chart of a method for overtaking apreceding vehicle according to one or more aspects of the disclosedsubject matter;

FIG. 11 is an algorithmic flow chart of a method for mapping a portionof the overtaking area corresponding to the host vehicle field of viewaccording to one or more aspects of the disclosed subject matter;

FIG. 12 is an algorithmic flow chart of a method for identifyingfeatures of the overtaking area according to one or more aspects of thedisclosed subject matter;

FIG. 13 is an algorithmic flow chart of a method for safely overtaking apreceding vehicle according to one or more aspects of the disclosedsubject matter;

FIG. 14A illustrates an obstruction area according to one or moreaspects of the disclosed subject matter;

FIG. 14B illustrates an obstruction area according to one or moreaspects of the disclosed subject matter;

FIG. 15 is an algorithmic flow chart of a method for vehicle collisionavoidance according to one or more aspects of the disclosed subjectmatter;

FIG. 16 is an algorithmic flow chart of a method for mapping a portionof the obstruction area corresponding to the host vehicle field of viewaccording to one or more aspects of the disclosed subject matter;

FIG. 17 is an algorithmic flow chart of a method for identifying anyobstructions in the obstruction area according to one or more aspects ofthe disclosed subject matter;

FIG. 18 is an algorithmic flow chart of a method for determining whetherthe speed of the host vehicle is safe based on the driver field of viewaccording to one or more aspects of the disclosed subject matter;

FIG. 19 illustrates a hardware block diagram of processing circuitry ofthe host vehicle according to one or more exemplary aspects of thedisclosed subject matter.

DETAILED DESCRIPTION

The description set forth below in connection with the appended drawingsis intended as a description of various embodiments of the disclosedsubject matter and is not necessarily intended to represent the onlyembodiment(s). In certain instances, the description includes specificdetails for the purpose of providing an understanding of the disclosedsubject matter. However, it will be apparent to those skilled in the artthat embodiments may be practiced without these specific details. Insome instances, well-known structures and components may be shown inblock diagram form in order to avoid obscuring the concepts of thedisclosed subject matter.

Reference throughout the specification to “one embodiment” or “anembodiment” means that a particular feature, structure, characteristic,operation, or function described in connection with an embodiment isincluded in at least one embodiment of the disclosed subject matter.Thus, any appearance of the phrases “in one embodiment” or “in anembodiment” in the specification is not necessarily referring to thesame embodiment. Further, the particular features, structures,characteristics, operations, or functions may be combined in anysuitable manner in one or more embodiments. Further, it is intended thatembodiments of the disclosed subject matter can and do covermodifications and variations of the described embodiments.

It must be noted that, as used in the specification and the appendedclaims, the singular forms “a,” “an,” and “the” include plural referentsunless the context clearly dictates otherwise. That is, unless clearlyspecified otherwise, as used herein the words “a” and “an” and the likecarry the meaning of “one or more.” Additionally, it is to be understoodthat terms such as “left,” “right,” “front,” “rear,” “side,” and thelike that may be used herein, merely describe points of reference and donot necessarily limit embodiments of the disclosed subject matter to anyparticular orientation or configuration. Furthermore, terms such as“first,” “second,” “third,” etc., merely identify one of a number ofportions, components, points of reference, operations and/or functionsas described herein, and likewise do not necessarily limit embodimentsof the disclosed subject matter to any particular configuration ororientation.

Referring now to the drawings, wherein like reference numerals designateidentical or corresponding parts throughout the several views, FIG. 1illustrates an exemplary system 100 configured for improving safety invarious driving situations including navigating a traffic intersection,overtaking a preceding vehicle, and avoiding collisions with sudden slowand/or stopped traffic on a highway according to one or more aspects ofthe disclosed subject matter. As will be discussed in more detail later,one or more methods according to various embodiments of the disclosedsubject matter can be implemented using the system 100 or portionsthereof. Put another way, system 100, or portions thereof, can performthe functions or operations described herein regarding the variousmethods or portions thereof (including those implemented using anon-transitory computer-readable medium storing a program that, whenexecuted, configures or causes a computer to perform or causeperformance of the described method(s) or portions thereof).

The system 100 can include a plurality of sensors 110, processingcircuitry 120 (which can include internal and/or external memory), asteering actuator 130, a braking actuator 140, and an alert system 150.In an embodiment, the plurality of sensors 110, the processing circuitry120 (which can include internal and/or external memory), the steeringactuator 130, the braking actuator 140, and the alert system 150 can beimplemented in a stand-alone apparatus 102. For example, the pluralityof sensors 110, the steering actuator 130, the braking actuator 140, andthe alert system 150 can be communicably coupled to the stand-alongapparatus 102. The stand-alone apparatus 102 can be a host vehicleoperated by a driver. Alternatively, or additionally, the host vehicle102 can be an autonomous vehicle or a highly automated vehicle, forexample. For convenience and clarity in the description, the stand-aloneapparatus 102 may be referred to herein as the host vehicle 102, whereinthe host vehicle 102 may include at least partial autonomous vehiclecontrol via the steering actuator 130 and the braking actuator 140, forexample. Additionally, throughout the description, the term traffic canbe used to describe one or more vehicles, bikes, pedestrians, electricvehicles (e.g., electric cars/trucks, electric scooters, electricskateboards, etc.), obstructions, and the like. Additionally, the termvehicle can also be used to describe one or more vehicles, bikes,pedestrians, electric vehicles (e.g., electric cars/trucks, electricscooters, electric skateboards, etc.), obstructions, and the like.

Generally speaking, the processing circuitry 120 can improve the safetyin various driving situations including navigating a trafficintersection, overtaking a preceding vehicle, and avoiding collisionswith sudden slow and/or stopped traffic on a highway. In one embodiment,the processing circuitry 120 can reduce the possibility of a crash atintersections. Drivers rarely check the behavior of trafficintersections when they know they have priority at signalized orcontrolled intersections. For example, when a driver has the green lightat a traffic intersection, the driver enters an intersection withoutchecking the possibility that intersecting traffic may violateintersection priority (e.g., an intersecting vehicle runs a red light).These crashes happen most frequently when intersecting traffic is notvisible or observed. Accordingly, the processing circuitry 120 canassist in safely navigating traffic intersections.

More specifically, the processing circuitry 120 can receive trafficintersection information from the plurality of sensors 110. Theplurality of sensors 110 can include one or more imaging devices, LiDAR,RADAR, ultrasonic sensors, and the like to gather information about theenvironment surrounding the host vehicle 102. Using the trafficintersection information received from the plurality of sensors 110, theprocessing circuitry 120 can further evaluate the safety of the trafficintersection and assist the host vehicle 102 and/or the driver of thehost vehicle 120 in navigating the traffic intersection. The pluralityof sensors 110 can provide a host vehicle field of view which can beconstrained by limitations of the sensors. Based on the host vehiclefield of view, the processing circuitry 120 can estimate a driver fieldof view, and based on the driver field of view, the processing circuitry120 can determine if any vehicles could be hidden at the trafficintersection (e.g., a vehicle may be hidden behind another vehicle orfoliage, or a building, etc). In the even that a vehicle may be hidden,the processing circuitry can determine that the driver field of view isobstructed by the vehicle, and because the vehicle in the driver fieldof view may be blocking another vehicle (e.g., hidden vehicle), thedriver may enter the traffic intersection believing that it is safe.Accordingly, the processing circuitry 120 can prevent a potentialcollision by alerting and/or modifying the driver's operation of thehost vehicle 102.

FIG. 2 illustrates a traffic intersection 200 according to one or moreaspects of the disclosed subject matter. The traffic intersection 200can include a plurality of stopped vehicles 205 a, 205 b, and 205 c,where stopped vehicle 205 a is in a second right intersecting lane 215a, stopped vehicle 205 b is in a first oncoming lane 240 a (oncominglane 240 b is empty), and stopped vehicle 205 c is in a first leftintersecting lane 220. In this example, a second left intersecting lane215 b is empty. Additionally, a first right intersecting lane 210includes an obstructed vehicle 225 and a visible vehicle 235. Theobstructed vehicle 225 is hidden by the stopped vehicle 205 a.Additionally, a sensor coverage area 230 can correspond to a hostvehicle field of view defined by the limitations of the plurality ofsensors 110, for example, where the plurality of sensors 110 have apredetermined distance and width of view. In FIG. 2, the stoppedvehicles 205 a and 205 b, the obstructed vehicle 225, and the visiblevehicle 235 are in the host vehicle field of view 230. However, theobstructed vehicle 225 is hidden by the stopped vehicle 205 a. Asfurther described herein, the processing circuitry 120 can determinethat a vehicle could be hidden from view (e.g., obstructed vehicle 225)in the traffic intersection 200 and assist the host vehicle 102 innavigating the intersection safely. It should be appreciated that thetraffic intersection 200 is exemplary, and the processing circuitry 120can assist the host vehicle 102 in navigating a variety of trafficintersection configurations including various stopped, obstructed, andvisible vehicle locations.

FIG. 3 illustrates an algorithmic flow chart of a method for trafficintersection navigation according to one or more aspects of thedisclosed subject matter.

In S305, the processing circuitry 120 of the host vehicle 102 canmap-match the host vehicle location in response to approaching a trafficintersection (e.g., traffic intersection 200).

In S310, the host vehicle 102 can receive traffic intersectioninformation from the plurality of sensors 110 in response to approachingthe traffic intersection. Additionally, the plurality of sensors 110 canhave a predetermined field of view corresponding to a field of view ofthe host vehicle. In other words, the host vehicle field of view can beconstrained by the limitations of the plurality of sensors 102. Forexample, the plurality of sensors 102 may be limited to a predeterminedviewing distance and a predetermined viewing width. Additionally, theremay be one or more objects and/or obstructions in the host vehicle fieldof view that may constrain the host vehicle field of view. For example,a vehicle may be hidden by another vehicle within the host vehicle fieldof view, thereby limiting the host vehicle field of view.

In S315, the host vehicle 102 (e.g., via the processing circuitry 120)can estimate a driver field of view based on the host vehicle field ofview. For example, the predetermined distance and width of the hostvehicle field of view can be used to estimate a driver's field of viewfrom inside the host vehicle (e.g., a vehicle operator in the driver'sseat of the host vehicle). Additionally, if the host vehicle field ofview recognizes a potential obstruction, the host vehicle 102 may usethat information to estimate that the driver may not be able to see pastthe obstruction, which constrains the driver's field of view.

In S320, the processing circuitry 120 can determine whether navigatingthrough the traffic intersection is safe based on the driver field ofview. If it is determined that navigating through the trafficintersection is safe based on the driver field of view, the process canend. However, if it is determined that navigating through the trafficintersection is not safe based on the driver field of view, the hostvehicle 102 can modify the driver's operation in S325.

In S325, the host vehicle 102 can modify driver operation in response toa determination that navigation through the traffic intersection is notsafe based on the driver field of view. For example, the host vehicle102 (e.g., by the processing circuitry 120) can alert the driver toinform the driver that navigating the intersection is not safe and/orautomatically modify (e.g., reduce) the driving speed of the hostvehicle 102 (e.g., by the braking actuator 140). After modifying thedriver operation in S325, the processing can end.

FIG. 4 illustrates an algorithmic flow chart of a method for determiningintersection priority according to one or more aspects of the disclosedsubject matter.

In S405, the processing circuitry 120 can identify the traffic lightpriority of the intersection based on the traffic intersectioninformation (e.g., the traffic intersection information received fromthe plurality of sensors in S310 in FIG. 3).

In S410, the processing circuitry 120 can identify the stop signpriority of the intersection based on the traffic intersectioninformation (e.g., the traffic intersection information received fromthe plurality of sensors in S310 in FIG. 3).

In S415, the processing circuitry 120 can identify an intersectionpriority of the entire intersection based on the traffic light priorityin S405 and/or the stop sign priority in S410 based on the set up of theintersection. After the intersection priority is identified, the processcan end.

FIG. 5 illustrates an algorithmic flow chart of a method for receivingthe traffic intersection information according to one or more aspects ofthe disclosed subject matter. For example, the method for receiving thetraffic intersection information can correspond to S310 in FIG. 3.

In S505, the plurality of sensors 110 can scan the traffic intersection.The information gathered by the plurality of sensors 110 can includevarious information regarding the set up and logistics of theintersection (e.g., intersection priority) by identifying the timing ofthe lights and/or stop signs, the number and position of vehicles,bikes, pedestrians, etc., and the like.

In S510, the processing circuitry 120 can identify all intersectinglanes (e.g., intersecting lanes 210, 215 a, 215 b, and 220) in thetraffic intersection based on the scan.

In S515, the processing circuitry 120 can identify all oncoming lanes inthe traffic intersection based on the scan (e.g., oncoming lanes 240 a,240 b). After identifying the oncoming lanes in the trafficintersection, the process can end.

FIG. 6 is an algorithmic flow chart of a method for mapping the hostvehicle field of view according to one or more aspects of the disclosedsubject matter.

In S605, the processing circuitry 120 can compare one or more identifiedintersecting lanes (e.g., the identified intersecting lanes received aspart of the traffic intersection information) with a map of the trafficintersection from the map-matched host vehicle location.

In S610, the processing circuitry 120 can compare one or more identifiedoncoming lanes (e.g., the identified oncoming lanes received as part ofthe traffic intersection information) with a map of the trafficintersection from the map-matched host vehicle location.

In S615, the processing circuitry 120 can map one or more intersectinglanes and oncoming lanes in the host vehicle field of view. In otherwords, based on comparing the map of the traffic intersection with thehost vehicle field of view, the one or more intersecting and oncominglanes that are in the host vehicle field of view can be identified.After mapping the one or more intersecting lanes and oncoming lanes inthe host vehicle field of view, the process can end.

FIG. 7 illustrates an algorithmic flow chart of a method for safelynavigating a traffic intersection according to one or more aspects ofthe disclosed subject matter. In FIG. 7, steps S705 through S725 cancorrespond to S320 and steps S730 and S735 can correspond to S325, forexample.

In S705, the processing circuitry 120 can identify any preceding trafficbased on the information received from the plurality of sensors 110. Forexample, preceding traffic can be any traffic in front of the hostvehicle 102. Additionally, traffic can correspond to one vehicle ormultiple vehicles. Further, traffic may also refer to one or morepedestrians, bikes, electric vehicles (e.g., electric skateboards,electric scooters, etc.), obstructions, and the like.

In S710, the processing circuitry 120 can identify any traffic behindthe host vehicle based on the information received from the plurality ofsensors 110.

In S715, the processing circuitry 120 can determine whether the hostvehicle 102 has priority in the traffic intersection based on thetraffic intersection information including traffic light priority andstop sign priority, for example. If the host vehicle 102 does not havepriority, the process can return to S715 to continue checking whetherthe host vehicle 102 has priority. If the host vehicle 102 does havepriority, the process can continue to identify traffic in each of one ormore intersecting lanes and one or more oncoming lanes in S720.

In S720, the processing circuitry 120 can identify vehicles and/ortraffic in each of one or more intersecting lanes and one or moreoncoming lanes. The vehicles can be identified based on the receivedtraffic intersection information which is based on the plurality ofsensors 110, for example.

In S725, the processing circuitry 120 can determine if any traffic couldbe hidden by the identified vehicles or other obstacles (e.g.,buildings, trees, shrubs, foliage, signs, walls, etc.) based on the hostvehicle field of view and whether the vehicles that could be hidden arein an unblocked lane. In other words, the processing circuitry 120 canrecognize, based on various information including the host vehicle fieldof view, the identified vehicles (or other obstacles) in the hostvehicle field of view, and the set-up of the traffic intersection,whether another vehicle could be hidden by one of the identifiedvehicles or other obstacles, and particularly, whether the potentiallyhidden vehicle would be in an unblocked lane. A hidden vehicle in anunblocked may be dangerous because it could enter the trafficintersection even when the hidden vehicle does not have trafficintersection priority. By recognizing that vehicles may be hidden behindthe identified vehicles, the processing circuitry 120 can modify thedriver's operation of the host vehicle 102 to prevent a collision andgenerally assist in safely navigating the traffic intersection. Inresponse to a determination that a vehicle could not be hidden, theprocess can end. However, in response to a determination that a vehiclecould be hidden and/or in an unblocked lane, the host vehicle 102 canperform one or more of alerting the driver in S730 and automaticallymodifying the driving speed of the host vehicle 102 in S735.

In S730, the processing circuitry 120 can alert the driver in responseto the determination that vehicles could be hidden in unblocked lanes.The alert can include one or more of audio, visual, and tactile alertsinforming the driver that navigating the traffic intersection is notsafe. For example, navigating the intersection may not be safe based onthe host vehicle's current speed because if a hidden vehicle were toenter the traffic intersection without priority, the host vehicle 102and/or the driver of the host vehicle 102 would not be able to react intime, which may lead to a collision.

In S735, the processing circuitry 120 can automatically modify a drivingspeed of the host vehicle 102 in response to the determination thatvehicles could be hidden in unblocked lanes. For example, the drivingspeed of the host vehicle may be reduced automatically (e.g., by thebraking actuator 140) to provide the host vehicle 102 and/or the driverof the host vehicle 102 more time to react to a potentially hiddenvehicle entering the intersection without priority. After automaticallymodifying the host vehicle driving speed, the process can end. It shouldbe appreciated that S730 and S735 may both occur, or optionally, one ofS730 or S735 can occur in response to the determination that thenavigating the traffic intersection is not safe, which can be selectedahead of time by the driver, for example.

FIG. 8A illustrates an overtaking area 800 according to one or moreaspects of the disclosed subject matter. In FIG. 8A, passing isprohibited in the overtaking area. The host vehicle 102 is behind apreceding vehicle 805. However, a host vehicle field of view 810 isobstructed by the preceding vehicle 805. An obstructed portion 820corresponds to a portion of the host vehicle field of view 810obstructed by the preceding vehicle 805. Additionally, an oncomingvehicle 815 is in the obstructed portion 820. Accordingly, the oncomingvehicle 815 is hidden in the overtaking area because the oncomingvehicle 815 is obstructed from the host vehicle 102. Even thoughovertaking the preceding vehicle is prohibited in the overtaking area inFIG. 8A, the processing circuitry 120 can assist in safely overtakingthe preceding vehicle by alerting and/or preventing the host vehicle 102from overtaking the preceding vehicle 805 because there may be anothervehicle hidden in the overtaking area (e.g., oncoming vehicle 815).

FIG. 8B illustrates an overtaking area 800 according to one or moreaspects of the disclosed subject matter. In FIG. 8B, overtaking apreceding vehicle is allowed. The description of the overtaking area 800is the same as in FIG. 8A other than that overtaking the precedingvehicle is allowed. However, for analogous reasons as described in FIG.8A, the processing circuitry 120 can prevent the host vehicle 102 fromovertaking the preceding vehicle 805 in FIG. 8B because another vehicle(e.g., oncoming vehicle 815) could be hidden in the overtaking area 800.It should be appreciated that the overtaking area 800 in FIGS. 8A and 8Bis exemplary, and the processing circuitry 120 can assist the hostvehicle 102 in various overtaking situations including various numbersof preceding vehicles, road geometries, topography, and the like.

FIG. 9 illustrates an exemplary host vehicle field of view 900 of thehost vehicle 102 and a driver field of view 905 of a driver 910according to one or more aspects of the disclosed subject matter. Forexample, the plurality of sensors 110 can combine to form the hostvehicle field of view 900. The plurality of sensors 110 may have variouswidth and distance limitations to the field of view. Additionally, thedriver field of view 905 can be estimate based on the host vehicle fieldof view 900. For example, the processing circuitry 120 can infer that ifa portion of the host vehicle field of view 900 is obstructed, thedriver field of view 905 is also obstructed in the same way.Additionally, if a portion of the environment of host vehicle 102 isoutside the host vehicle field of view 900, it may also be outside thedriver field of view 905. It should be appreciated that the host vehiclefield of view 900 is exemplary and any host vehicle fields of view basedon various combinations of sensors in the plurality of sensors 110 canbe configured for use with the system 100.

FIG. 10 is an algorithmic flow chart of a method for overtaking apreceding vehicle according to one or more aspects of the disclosedsubject matter.

In S1005, the processing circuitry 120 of the host vehicle 102 canmap-match the host vehicle location in response to approaching precedingvehicle (e.g., preceding vehicle 805).

In S1010, the host vehicle 102 can receive overtaking information fromthe plurality of sensors 110 in response to approaching the precedingvehicle. The overtaking information can include various data gathered bythe plurality of sensors 110 including information about the environmentsurrounding the host vehicle 102 (e.g., identifying preceding vehicles,topology of the overtaking area, and the like as further describedherein). Using the overtaking information received from the plurality ofsensors 110, the processing circuitry 120 can further evaluate thesafety of the overtaking area and assist the host vehicle 102 and/or thedriver of the host vehicle 120 in navigating the traffic intersection.Additionally, the plurality of sensors 110 can have a predeterminedfield of view corresponding to a field of view of the host vehicle asfurther described herein.

In S1015, the host vehicle 102 (e.g., via the processing circuitry 120)can estimate a driver field of view based on the host vehicle field ofview as further described herein.

In S1020, the processing circuitry 120 can determine whether overtakingthe preceding vehicle is safe based on the driver field of view. If itis determined that overtaking the preceding vehicle is safe based on thedriver field of view, the process can end. However, if it is determinedthat overtaking the preceding vehicle is not safe based on the driverfield of view, the host vehicle 102 can modify the driver's operation inS1025.

In S1025, the host vehicle 102 can modify driver operation in responseto a determination that navigation through the traffic intersection isnot safe based on the driver field of view. For example, the hostvehicle 102 (e.g., by the processing circuitry 120) can alert the driverto inform the driver that overtaking the preceding vehicle is not safeand/or automatically actuate steering of the host vehicle 102 (e.g., bythe steering actuator 130). After modifying the driver operation inS325, the process can end.

FIG. 11 is an algorithmic flow chart of a method for mapping a portionof the overtaking area (e.g., overtaking area 800) corresponding to thehost vehicle field of view according to one or more aspects of thedisclosed subject matter. In FIG. 11, steps S1105 and S1110 cancorrespond to S1010, for example.

In S1105, the plurality of sensors 110 can scan the overtaking area. Theinformation gathered by the plurality of sensors 110 can includeinformation regarding any features of the overtaking area. For example,the plurality of sensors 110 can gather information about the traffic inthe overtaking area, a topology of the overtaking area, a road type ofthe overtaking area, and the like.

In S1110, the processing circuitry 120 can identify features of theovertaking area based on the scan in S1105. The features identified caninclude traffic in the overtaking area, a specific topology of theovertaking area, the road type of the overtaking area, and the like asfurther described herein.

In S1115, the processing circuitry 120 can compare the scannedovertaking area with a map of the overtaking area from the map-matchedhost vehicle location.

In S1120, the processing circuitry 120 can map a portion of theovertaking area corresponding to the host vehicle field of view based onthe comparison of the scanned overtaking area with the map of theovertaking area from the map-matched host vehicle location. In otherwords, based on comparing the map of the overtaking area with the hostvehicle field of view, the features that are specifically in the portionof the overtaking area corresponding to the host vehicle field of viewcan be identified. After mapping the portion of the overtaking areacorresponding to the host vehicle field of view, the process can end.

FIG. 12 is an algorithmic flow chart of a method for identifyingfeatures of the overtaking area according to one or more aspects of thedisclosed subject matter. In FIG. 12, steps S1205 through S1220 cancorrespond to S1110.

In S1205, the processing circuitry 120 can identify a type of roadwaythe host vehicle is traveling on in the overtaking area based on theinformation received from the plurality of sensors 110 from the scan ofthe overtaking area.

In S1210, the processing circuitry 120 can identify a road geometry ofthe overtaking area based on the information received from the pluralityof sensors 110 from the scan of the overtaking area. For example,information about a curvature of the road and/or a location of thevehicle with respect to any changes in the road geometry received fromthe plurality of sensors 110 can be compared with the map of theovertaking area to identify the road geometry of the overtaking area(e.g., a curve in the road that could block a driver's field of view andprevent the driver from seeing an oncoming vehicle).

In S1215, the processing circuitry 120 can identify a topology of theovertaking area based on the information received from the plurality ofsensors 110 from the scan of the overtaking area. Alternatively, oradditionally, topology of the overtaking area can be identified based onthe map from the map-matched location of the host vehicle 102. Forexample, the area surrounding the location of the host vehicle may havewell known topology that may constrain the host vehicle field of viewand/or the driver field of view (e.g., hills, trees, etc.).

In S1220, the processing circuitry 120 can identify a lane marker typein the overtaking area based on the information received from theplurality of sensors 110 from the scan of the overtaking area. After thelane marker type in the overtaking area is identified, the process canend.

FIG. 13 is an algorithmic flow chart of a method for preventing unsafelyovertaking a preceding vehicle according to one or more aspects of thedisclosed subject matter. In FIG. 13, steps S1305 through S1315 cancorrespond to S1020 and steps S1320 and S1325 can correspond to S1025,for example.

In S1305, the processing circuitry 120 can identify any vehicles in theportion of the overtaking area corresponding to the host vehicle fieldof view based on the overtaking information received from the pluralityof sensors 110.

In S1310, the processing circuitry 120 can identify any topology in theportion of the overtaking area corresponding to the host vehicle fieldof view based on the overtaking information received from the pluralityof sensors 110 and/or the map information where the comparison of themap of the overtaking area from the map-matched host vehicle locationcan assist in identifying any topology in the overtaking area that isspecifically in the host vehicle field of view.

In S1315, the processing circuitry 120 can determine if any vehiclescould be hidden in the overtaking area. For example, the processingcircuitry 120 can determine if one or more vehicles could be hidden byone or more of the identified vehicles in the host vehicle field ofview, the road geometry of the overtaking area (e.g., the road curvesoutside the host vehicle field of view), and the topology in the hostvehicle field of view (e.g., a hill in the overtaking area blocks atleast a portion of the host vehicle field of view). In other words,determining whether any vehicles could be hidden in the overtaking areacan assist in determining whether overtaking a preceding vehicle is safebecause if a vehicle could be hidden then overtaking the precedingvehicle could be dangerous and should be avoided until it is safe toovertake the preceding vehicle. In response to a determination that avehicle could not be hidden (e.g., nothing in the overtaking area couldbe blocking the host vehicle and/or driver field of view), the processcan end. However, in response to a determination that a vehicle could behidden, the host vehicle 102 can perform one or more of alerting thedriver in S1320 and automatically actuating the steering of the hostvehicle 102 in S1325.

In S1320, the processing circuitry 120 can alert the driver in responseto the determination that one or more vehicles could be hidden in theovertaking area. The alert can include one or more of audio, visual, andtactile alerts informing the driver that overtaking the precedingvehicle is not safe. For example, overtaking the preceding vehicle maynot be safe because a hidden vehicle may prevent the host vehicle fromsafely executing the overtaking maneuver, which may lead to a collision.

In S1325, the processing circuitry 120 can automatically actuatesteering (e.g., by the steering actuator 130) of the host vehicle 102 inresponse to the determination that one or more vehicles could be hiddenin the overtaking area. For example, the steering may be actuatedautomatically to prevent the host vehicle 102 and/or the driver of thehost vehicle 102 from executing the overtaking maneuver. It should beappreciated that other vehicle controls can be configured to assist,independently or in combination, in modifying the host vehicle operation(e.g., acceleration, deceleration, braking, etc.) as needed. Forexample, deceleration can occur by braking, but may also correspond toreducing speed without braking (e.g., reducing or cutting power to anengine of the host vehicle). After automatically actuating steering ofthe host vehicle, the process can end. It should be appreciated thatS1320 and S1325 may both occur, or, optionally, one of S1320 or S1325can occur in response to the determination that overtaking the precedingvehicle is not safe, which can be selected ahead of time by the driver,for example.

FIG. 14A illustrates an obstruction area 1400 according to one or moreaspects of the disclosed subject matter. In FIG. 14A, the obstructionarea 1400 includes traffic occlusion. In other words, the host vehiclefield of view is obstructed due to one or more preceding vehicles. Theobstruction area 1400 includes a fast vehicle 1405, a first slow vehicle1410 a, a second slow vehicle 1410 b, a first stopped vehicle 1415 a,and a second stopped vehicle 1415 b, for example. Due to the precedingvehicle being the fast vehicle 1405, the driver's field of view is notonly blocked from seeing the stopped vehicles 1415 a, 1415 b, but alsothe fast vehicle 1405 appears to be operating at a normal speed with noindication of the upcoming slow and stopped traffic. As furtherdescribed herein, the processing circuitry 120 can assist the hostvehicle 102 by recognizing that the host vehicle field of view and/orthe driver field of view is obstructed (e.g., traffic occlusion), andreduce the speed of the host vehicle 102 accordingly to prevent acollision with potentially slow and/or stopped traffic. It should beappreciated that the traffic occlusion example is exemplary and theprocessing circuitry 120 can assist the host vehicle 102 with varioustraffic occlusion situations including any number of fast, slow, andstopped vehicles.

FIG. 14B illustrates an obstruction area 1402 according to one or moreaspects of the disclosed subject matter. In FIG. 14B, the obstructionarea 1402 includes landscape (e.g., topology) occlusion 1435. In otherwords, the host vehicle field of view is obstructed due to a landscapeand/or a topology of the obstruction area 1402. The obstruction area1400 includes a fast vehicle 1420, a slow vehicle 1425, and a stoppedvehicle 1430, for example. Due to the topology (e.g., landscapeocclusion 1435) of the obstruction area 1400, the host vehicle field ofview is obstructed and the host vehicle 102 may not be aware that slowand stopped vehicles are ahead. As further described herein, theprocessing circuitry 120 can assist the host vehicle 102 by recognizingthat the host vehicle field of view and/or the driver field of view isobstructed (e.g., landscape occlusion 1435), and reduce the speed of thehost vehicle 102 accordingly to prevent a collision with potentiallyslow and/or stopped traffic. It should be appreciated that the landscapeocclusion 1435 example is exemplary and the processing circuitry 120 canassist the host vehicle 102 with various landscape occlusion situationsincluding any type of landscape occlusion (e.g., hill, foliage, trees,walls, etc.) and any number of fast, slow, and stopped vehicles.

FIG. 15 is an algorithmic flow chart of a method for vehicle collisionavoidance according to one or more aspects of the disclosed subjectmatter.

In S1505, the processing circuitry 120 can map-match a location of thehost vehicle 102 while the host vehicle is operating on a highway.

In S1510, the processing circuitry 120 can receive obstructioninformation from the plurality of sensors 110. The obstructioninformation can include information regarding an obstruction area.Additionally, the plurality of sensors 110 can have a predeterminedfield of view corresponding to a field of view of the host vehicle asfurther described herein.

In S1515, the host vehicle 102 (e.g., via the processing circuitry 120)can estimate a driver field of view based on the host vehicle field ofview as further described herein.

In S1520, the processing circuitry 120 can determine whether a speed ofthe host vehicle 102 is safe based on the driver field of view and/orthe obstruction information. In response to a determination that thespeed of the host vehicle 102 is safe, the process can end. However, inresponse to a determination that the speed of the host vehicle 102 isnot safe, the host vehicle 102 can modify driver operation of the hostvehicle field of view in S1525. Additionally, in one embodiment, aheadway (average interval of time between vehicles moving in the samedirection on the same route) of the host vehicle 102 can be used todetermine whether driver operation of the host vehicle should bemodified. The headway can be used in combination with the speed of thehost vehicle based on their close relationship (e.g., when speed isincreased the headway is decreased).

In S1525, the host vehicle 102 can modify driver operation in responseto a determination that the speed of the host vehicle 102 is not safebased on the driver field of view and/or the obstruction information.For example, the host vehicle 102 (e.g., by the processing circuitry120) can alert the driver to inform the driver that the speed of thehost vehicle 102 is not safe and/or automatically actuate a brakingsystem of the host vehicle 102 (e.g., reduce speed). After modifying thedriver operation in S325, the process can end.

FIG. 16 is an algorithmic flow chart of a method for mapping a portionof the obstruction area (e.g., obstruction area 1400, 1402)corresponding to the host vehicle field of view according to one or moreaspects of the disclosed subject matter. In FIG. 16, steps S1605 andS1610 can correspond to S1510, for example.

In S1605, the plurality of sensors 110 can scan the obstruction area.The information gathered by the plurality of sensors 110 can includeinformation regarding any traffic in the obstruction area and anyfeatures of the obstruction area. For example, the plurality of sensors110 can gather information about one or more vehicles in the obstructionarea, a topology of the obstruction area, and the like.

In S1610, the processing circuitry 120 can identify features of theobstruction area based on the scan in S1605. The features identified caninclude any traffic in the obstruction area (e.g., one or more vehicles,bikes, pedestrians, electric vehicles, etc.), a specific topology of theobstruction area (e.g., hills, foliage, walls, etc.), and the like.

In S1615, the processing circuitry 120 can compare the scannedobstruction area with a map of the obstruction area from the map-matchedhost vehicle location.

In S1620, the processing circuitry 120 can map a portion of theobstruction area corresponding to the host vehicle field of view basedon the comparison of the scanned obstruction area with the map of theobstruction area from the map-matched host vehicle location. In otherwords, based on comparing the map of the obstruction area with the hostvehicle field of view, the features that are specifically in the portionof the obstruction area corresponding to the host vehicle field of viewcan be identified. After mapping the portion of the obstruction areacorresponding to the host vehicle field of view, the process can end.

FIG. 17 is an algorithmic flow chart of a method for identifying anyobstructions in the obstruction area according to one or more aspects ofthe disclosed subject matter. In FIG. 17, steps S1705 and S1710 cancorrespond to S1610 in FIG. 16.

In S1705, the processing circuitry 120 can identify a topology of theobstruction area based on scan of the obstruction area. Alternatively,or additionally, topology of the obstruction area can be identifiedbased on the map from the map-matched location of the host vehicle 102.For example, the area surrounding the location of the host vehicle mayhave well known topology that may obstruct the host vehicle field ofview and/or the driver field of view (e.g., hills, trees, foliage,walls, etc.).

In S1710, the processing circuitry 120 can identify any weatherobstructing the driver field of view based on the information receivedfrom the plurality of sensors 110. For example, the plurality of sensors110 can determine if it is raining (e.g., imaging device, windshieldwiper sensor, etc.), and because the rain and/or windshield wipers mayobstruct the driver field of view, the weather obstructing the driverfield of view can be taken into account when determining whether thespeed of the host vehicle 102 is safe. Additional weather obstructionsmay include sunlight, fog, snow, and the like, for example. Afteridentifying any weather obstructing the driver field of view, theprocess can end.

FIG. 18 is an algorithmic flow chart of a method for determining whetherthe speed of the host vehicle is safe based on the driver field of viewaccording to one or more aspects of the disclosed subject matter. InFIG. 18, steps S1805 through S1820 can correspond to S1520 and stepsS1825 and S1830 can correspond to S1525.

In S1805, the processing circuitry 120 can identify any vehicles in theportion of the obstruction area corresponding to the host vehicle fieldof view based on the obstruction information received from the pluralityof sensors 110.

In S1810, the processing circuitry 120 can identify any topology in theportion of the obstruction area corresponding to the host vehicle fieldof view based on the obstruction information received from the pluralityof sensors 110 and/or the map information where the comparison of themap of the obstruction area from the map-matched host vehicle locationcan assist in identifying any topology in the obstruction area that isspecifically in the host vehicle field of view.

In S1815, the processing circuitry 120 can determine whether anyvehicles could be hidden in the obstruction area. For example, theprocessing circuitry 120 can determine if one or more vehicles could behidden by one or more of the identified vehicles in the host vehiclefield of view and/or the topology in the host vehicle field of view(e.g., a hill in the obstruction area blocks at least a portion of thehost vehicle field of view). In other words, determining whether anyvehicles could be hidden in the obstruction area can assist indetermining whether the speed of the host vehicle 102 is safe because ifa vehicle could be hidden then the speed of the host vehicle 102 couldbe dangerous if the one or more hidden vehicle is driving much slower oris stopped. For example, due to an accident on a highway, traffic may beslow and or stopped, and when the slow and/or stopped traffic is hiddenbehind other vehicles in front of the host vehicle 102 and/or thetopology of the area, the speed of the host vehicle 102 should bereduced until the processing circuitry 120 can confirm (e.g., via theplurality of sensors) that no vehicles are hidden in the obstructionarea. In response to a determination that a vehicle could not be hidden(e.g., nothing in the obstruction area could be blocking the hostvehicle and/or driver field of view), the process can end. However, inresponse to a determination that one or more vehicles could be hidden,the processing circuitry 120 can determine whether the host vehicle 102could stop in time to prevent a collision in S1820.

In S1820, the processing circuitry 120 can determine whether the hostvehicle 102 could stop in time to prevent a collision based on the speedof the host vehicle 102 and the distance to a potentially hiddenvehicle, for example. In response to a determination that the hostvehicle 102 could stop in time, the process can end. However, inresponse to a determination that the host vehicle 102 could not stop intime, the host vehicle 102 can perform one or more of alerting thedriver in S1825 and automatically actuating a braking system of the hostvehicle 102 in S1830.

In S1825, the processing circuitry 120 can alert the driver in responseto the determination that one or more vehicles could be hidden in theobstruction area. The alert can include one or more of audio, visual,and tactile alerts informing the driver that the speed of the hostvehicle 102 is not safe. For example, the speed of the host vehicle 102may not be safe because if there is a hidden vehicle, the host vehicle102 may not be able to stop in time to avoid a collision.

In S1830, the processing circuitry 120 can automatically actuate abraking system (e.g., by the braking actuator 140) of the host vehicle102 in response to the determination that one or more vehicles could behidden in the obstruction area. For example, the braking may be actuatedautomatically to reduce the speed of the host vehicle 102 so that thehost vehicle 102 would be able to stop in time to avoid a collision ifthere was one or more hidden vehicles in the obstruction area. Afterautomatically actuating the braking system of the host vehicle 102, theprocess can end. It should be appreciated that S1825 and S1830 may bothoccur, or, optionally, one of S1825 or S1830 can occur in response tothe determination that the speed of the host vehicle 102 is not safe,which can be selected ahead of time by the driver, for example.

In the above description of FIGS. 3-7, 10-13, and 15-18, any processes,descriptions or blocks in flowcharts can be understood as representingmodules, segments or portions of code which include one or moreexecutable instructions for implementing specific logical functions orsteps in the process, and alternate implementations are included withinthe scope of the exemplary embodiments of the present advancements inwhich functions can be executed out of order from that shown ordiscussed, including substantially concurrently or in reverse order,depending upon the functionality involved, as would be understood bythose skilled in the art. The various elements, features, and processesdescribed herein may be used independently of one another, or may becombined in various ways. All possible combinations and sub-combinationsare intended to fall within the scope of this disclosure.

Next, a hardware description of the processing circuitry 120 accordingto exemplary embodiments is described with reference to FIG. 19. Thehardware description described herein can also be a hardware descriptionof the processing circuitry. In FIG. 19, the processing circuitry 120includes a CPU 1900 which performs one or more of the processesdescribed above/below. The process data and instructions may be storedin memory 1902. These processes and instructions may also be stored on astorage medium disk 1904 such as a hard drive (HDD) or portable storagemedium or may be stored remotely. Further, the claimed advancements arenot limited by the form of the computer-readable media on which theinstructions of the inventive process are stored. For example, theinstructions may be stored on CDs, DVDs, in FLASH memory, RAM, ROM,PROM, EPROM, EEPROM, hard disk or any other information processingdevice with which the processing circuitry 120 communicates, such as aserver or computer.

Further, the claimed advancements may be provided as a utilityapplication, background daemon, or component of an operating system, orcombination thereof, executing in conjunction with CPU 1900 and anoperating system such as Microsoft Windows, UNIX, Solaris, LINUX, AppleMAC-OS and other systems known to those skilled in the art.

The hardware elements in order to achieve the processing circuitry 120may be realized by various circuitry elements. Further, each of thefunctions of the above described embodiments may be implemented bycircuitry, which includes one or more processing circuits. A processingcircuit includes a particularly programmed processor, for example,processor (CPU) 1900, as shown in FIG. 19. A processing circuit alsoincludes devices such as an application specific integrated circuit(ASIC) and conventional circuit components arranged to perform therecited functions.

In FIG. 19, the processing circuitry 120 includes a CPU 1900 whichperforms the processes described above. The processing circuitry 120 maybe a general-purpose computer or a particular, special-purpose machine.In one embodiment, the processing circuitry 120 becomes a particular,special-purpose machine when the processor 1900 is programmed to improvethe safety in various driving situations including navigating a trafficintersection, overtaking a preceding vehicle, and avoiding collisionswith sudden slow and/or stopped traffic on a highway (and in particular,any of the processes discussed with reference to FIGS. 3-7, 10-13, and15-18).

Alternatively, or additionally, the CPU 1900 may be implemented on anFPGA, ASIC, PLD or using discrete logic circuits, as one of ordinaryskill in the art would recognize. Further, CPU 1900 may be implementedas multiple processors cooperatively working in parallel to perform theinstructions of the inventive processes described above.

The processing circuitry 120 in FIG. 19 also includes a networkcontroller 1906, such as an Intel Ethernet PRO network interface cardfrom Intel Corporation of America, for interfacing with network 1928. Ascan be appreciated, the network 1928 can be a public network, such asthe Internet, or a private network such as an LAN or WAN network, or anycombination thereof and can also include PSTN or ISDN sub-networks. Thenetwork 1928 can also be wired, such as an Ethernet network, or can bewireless such as a cellular network including EDGE, 3G and 4G wirelesscellular systems. The wireless network can also be WiFi, Bluetooth, orany other wireless form of communication that is known.

The processing circuitry 120 further includes a display controller 1908,such as a graphics card or graphics adaptor for interfacing with display1910, such as a monitor. A general purpose I/O interface 1912 interfaceswith a keyboard and/or mouse 1914 as well as a touch screen panel 1916on or separate from display 1910. General purpose I/O interface alsoconnects to a variety of peripherals 1918 including printers andscanners.

A sound controller 1920 is also provided in the processing circuitry 120to interface with speakers/microphone 1922 thereby providing soundsand/or music.

The general purpose storage controller 1924 connects the storage mediumdisk 1904 with communication bus 1926, which may be an ISA, EISA, VESA,PCI, or similar, for interconnecting all of the components of theprocessing circuitry 120. A description of the general features andfunctionality of the display 1910, keyboard and/or mouse 1914, as wellas the display controller 1908, storage controller 1924, networkcontroller 1906, sound controller 1920, and general purpose I/Ointerface 1912 is omitted herein for brevity as these features areknown.

The exemplary circuit elements described in the context of the presentdisclosure may be replaced with other elements and structureddifferently than the examples provided herein. Moreover, circuitryconfigured to perform features described herein may be implemented inmultiple circuit units (e.g., chips), or the features may be combined incircuitry on a single chipset.

The functions and features described herein may also be executed byvarious distributed components of a system. For example, one or moreprocessors may execute these system functions, wherein the processorsare distributed across multiple components communicating in a network.The distributed components may include one or more client and servermachines, which may share processing, in addition to various humaninterface and communication devices (e.g., display monitors, smartphones, tablets, personal digital assistants (PDAs)). The network may bea private network, such as a LAN or WAN, or may be a public network,such as the Internet. Input to the system may be received via directuser input and received remotely either in real-time or as a batchprocess. Additionally, some implementations may be performed on modulesor hardware not identical to those described. Accordingly, otherimplementations are within the scope that may be claimed.

Having now described embodiments of the disclosed subject matter, itshould be apparent to those skilled in the art that the foregoing ismerely illustrative and not limiting, having been presented by way ofexample only. Thus, although particular configurations have beendiscussed herein, other configurations can also be employed. Numerousmodifications and other embodiments (e.g., combinations, rearrangements,etc.) are enabled by the present disclosure and are within the scope ofone of ordinary skill in the art and are contemplated as falling withinthe scope of the disclosed subject matter and any equivalents thereto.Features of the disclosed embodiments can be combined, rearranged,omitted, etc., within the scope of the invention to produce additionalembodiments. Furthermore, certain features may sometimes be used toadvantage without a corresponding use of other features. Accordingly,Applicant(s) intend(s) to embrace all such alternatives, modifications,equivalents, and variations that are within the spirit and scope of thedisclosed subject matter.

The invention claimed is:
 1. A host vehicle, comprising: a plurality ofsensors communicably coupled to the host vehicle, and processingcircuitry configured to: map-match a location of the host vehicle inresponse to approaching a traffic intersection, receive trafficintersection information from the plurality of sensors in response toapproaching the traffic intersection, the plurality of sensors having apredetermined field of view corresponding to a field of view of the hostvehicle, estimate a driver field of view based on the field of view ofthe host vehicle, determine whether or not the host vehicle has priorityat the traffic intersection, when it is determined that the host vehicledoes have the priority at the traffic intersection, determine whether ornot navigating through the traffic intersection is safe based on thedriver field of view, when it is determined that the host vehicle doesnot have the priority, determine whether or not the host vehicle has thepriority at the traffic intersection until it is determined that thehost vehicle has the priority at the traffic intersection, and when itis determined that navigating through the traffic intersection is notsafe, automatically modify a driving speed of the host vehicle, whereindetermine whether or not navigating through the traffic intersection issafe includes determining whether or not any vehicles could be hidden,and when it is determined that any vehicles could be hidden, theprocessing circuitry is configured to automatically modify the drivingspeed of the host vehicle.
 2. The host vehicle of claim 1, wherein theprocessing circuitry is configured to determine whether or not the hostvehicle has the priority at the traffic intersection based on thetraffic intersection information.
 3. The host vehicle of claim 2,wherein the processing circuitry is configured to: identify trafficlight priority based on the traffic intersection information, identifystop sign priority based on the traffic intersection information, anddetermine whether or not the host vehicle has the priority at thetraffic intersection based on one or more of the traffic light priorityand the stop sign priority.
 4. The host vehicle of claim 1, wherein theprocessing circuitry is configured to: control the plurality of sensorsto scan the traffic intersection, identify all intersecting lanes in thetraffic intersection based on the scan, and identify all oncoming lanesin the traffic intersection based on the scan.
 5. The host vehicle ofclaim 4, wherein the processing circuitry is configured to: compare oneor more of the intersecting lanes with a map of the traffic intersectionfrom the location of the host vehicle, compare one or more of theoncoming lanes with the map of the traffic intersection, and map one ormore of the intersecting lanes and the oncoming lanes in the field ofview of the host vehicle.
 6. The host vehicle of claim 1, wherein theprocessing circuitry is configured to: identify any preceding traffic,identify any traffic behind the host vehicle, identify vehicles in eachof one or more intersecting lanes and one or more oncoming lanes, anddetermine if any of the one or more intersecting lanes and the one ormore oncoming lanes in an unblocked lane, wherein determine whether ornot navigating through the traffic intersection is safe includesdetermining whether or not the vehicles that could be hidden are in anunblocked lane.
 7. The host vehicle of claim 1, wherein the processingcircuitry is configured to: alert the driver when it is determined thatany vehicles could be hidden.
 8. The host vehicle of claim 6, whereinthe processing circuitry is configured to: when it is determined thatthe vehicles that could be hidden are in the unblocked lane,automatically modify the driving speed of the host vehicle, and when itis determined that the vehicles that could be hidden are not in theunblocked lane, not automatically modify the driving speed of the hostvehicle.
 9. A method for traffic intersection navigation for a hostvehicle, comprising: map-matching, by processing circuitry, a locationof the host vehicle in response to approaching a traffic intersection;receiving, by the processing circuitry, traffic intersection informationfrom a plurality of sensors in response to approaching the trafficintersection, the plurality of sensors having a predetermined field ofview corresponding to a field of view of the host vehicle; estimating,by the processing circuitry, a driver field of view based on the fieldof view of the host vehicle; determining, by the processing circuitry,whether or not the host vehicle has priority at the trafficintersection; determining, by the processing circuitry, whether or notnavigating through the traffic intersection is safe based on the driverfield of view when it is determined that the host vehicle does have thepriority at the traffic intersection; determining, by the processingcircuitry, whether or not the host vehicle has the priority at thetraffic intersection until it is determined that the host vehicle hasthe priority at the traffic intersection when it is determined that thehost vehicle does not have the priority; and automatically modifying, bythe processing circuitry, a driving speed of the host vehicle when it isdetermined that navigating through the traffic intersection is not safe,wherein determining whether or not navigating through the trafficintersection is safe includes determining whether or not any vehiclescould be hidden, and the method includes automatically modify thedriving speed of the host vehicle when it is determined that anyvehicles could be hidden.
 10. The method of claim 9, further comprising:determining whether or not the host vehicle has the priority at thetraffic intersection based on the traffic intersection information. 11.The method of claim 10, wherein determining intersection priorityfurther comprises: identifying traffic light priority based on thetraffic intersection information; identifying stop sign priority basedon the traffic intersection information; and determining whether or notthe host vehicle has the priority at the traffic intersection based onone or more of the traffic light priority and the stop sign priority.12. The method of claim 9, further comprising: scanning the trafficintersection; identifying all intersecting lanes in the trafficintersection based on the scanning; and identifying all oncoming lanesin the traffic intersection based on the scanning.
 13. The method ofclaim 12, further comprising: comparing one or more of the intersectinglanes with a map of the traffic intersection from the location of thehost vehicle; comparing one or more of the oncoming lanes with the mapof the traffic intersection; and mapping one or more of the intersectinglanes and the oncoming lanes in the field of view of the host vehicle.14. The method of claim 9, further comprising: identifying any precedingtraffic; identifying any traffic behind the host vehicle; identifyingvehicles in each of one or more intersecting lanes and one or moreoncoming lanes; and determining if any of the one or more intersectinglanes and the one or more oncoming lanes in an unblocked lane, whereindetermining whether or not navigating through the traffic intersectionis safe includes determining whether or not the vehicles that could behidden are in an unblocked lane.
 15. The method of claim 14, furthercomprising: automatically modifying the driving speed of the hostvehicle when it is determined that the vehicles that could be hidden arein the unblocked lane, and not automatically modify the driving speed ofthe host vehicle when it is determined that the vehicles that could behidden are not in the unblocked lane.
 16. A non-transitorycomputer-readable storage medium storing computer-readable instructionsthereon which, when executed by a computer, cause the computer toperform a method, the method comprising: map-matching a location of ahost vehicle in response to approaching a traffic intersection;receiving traffic intersection information from a plurality of sensorsin response to approaching the traffic intersection, the plurality ofsensors having a predetermined field of view corresponding to a field ofview of the host vehicle; estimating a driver field of view based on thefield of view of the host vehicle; determining whether or not the hostvehicle has priority at the traffic intersection; determining whether ornot navigating through the traffic intersection is safe based on thedriver field of view when it is determined that the host vehicle doeshave the priority at the traffic intersection; determining whether ornot the host vehicle has the priority at the traffic intersection untilit is determined that the host vehicle has the priority at the trafficintersection when it is determined that the host vehicle does not havethe priority; and automatically modifying a driving speed of the hostvehicle when it is determined that navigating through the trafficintersection is not safe, wherein determining whether or not navigatingthrough the traffic intersection is safe includes determining whether ornot any vehicles could be hidden, and the method includes automaticallymodify the driving speed of the host vehicle when it is determined thatany vehicles could be hidden.
 17. The non-transitory computer-readablestorage medium of claim 16, further comprising: identifying trafficlight priority based on the traffic intersection information;identifying stop sign priority based on the traffic intersectioninformation; and determining whether or not the host vehicle has thepriority at the traffic intersection based on one or more of the trafficlight priority and the stop sign priority.
 18. The non-transitorycomputer-readable storage medium of claim 16, further comprising:scanning the traffic intersection; identifying all intersecting lanes inthe traffic intersection based on the scanning; identifying all oncominglanes in the traffic intersection based on the scanning; comparing oneor more of the intersecting lanes with a map of the traffic intersectionfrom the location of the host vehicle; comparing one or more of theoncoming lanes with the map of the traffic intersection; and mapping oneor more of the intersecting lanes and the oncoming lanes in the field ofview of the host vehicle.
 19. The non-transitory computer-readablestorage medium of claim 16, further comprising: identifying anypreceding traffic; identifying any traffic behind the host vehicle;identifying vehicles in each of one or more intersecting lanes and oneor more oncoming lanes; and determining if any of the one or moreintersecting lanes and the one or more oncoming lanes in an unblockedlane, wherein determining whether or not navigating through the trafficintersection is safe includes determining whether or not the vehiclesthat could be hidden are in an unblocked lane.
 20. The non-transitorycomputer-readable storage medium of claim 19, further comprising:automatically modifying the driving speed of the host vehicle when it isdetermined that the vehicles that could be hidden are in the unblockedlane, and not automatically modify the driving speed of the host vehiclewhen it is determined that the vehicles that could be hidden are not inthe unblocked lane.